Natural language processing diagnosed behavioural disturbance phenotypes in the intensive care unit: characteristics, prevalence, trajectory, treatment, and outcomes.

Journal: Critical care (London, England)
PMID: 37925406

Abstract

BACKGROUND: Natural language processing (NLP) may help evaluate the characteristics, prevalence, trajectory, treatment, and outcomes of behavioural disturbance phenotypes in critically ill patients.

Authors

  • Marcus Young
    Data Analytics Research and Evaluation (DARE) Centre, Austin Health and The University of Melbourne, Austin Hospital, Melbourne, Heidelberg, VIC, Australia. marcus.young3@austin.org.au.
  • Natasha E Holmes
    Data Analytics Research and Evaluation (DARE) Centre, Austin Health and The University of Melbourne, Heidelberg, VIC, Australia.
  • Kartik Kishore
    Data Analytics Research and Evaluation (DARE) Centre, Austin Health and The University of Melbourne, Austin Hospital, Melbourne, Heidelberg, VIC, Australia.
  • Sobia Amjad
    Data Analytics Research and Evaluation (DARE) Centre, Austin Health and The University of Melbourne, Heidelberg, VIC, Australia.
  • Michele Gaca
    Data Analytics Research and Evaluation (DARE) Centre, Austin Health and The University of Melbourne, Heidelberg, VIC, Australia.
  • Ary Serpa Neto
    Data Analytics Research and Evaluation (DARE) Centre, Austin Health and The University of Melbourne, Heidelberg, VIC, Australia.
  • Michael C Reade
    Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.
  • Rinaldo Bellomo
    Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, VIC, Australia.

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